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Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy
This paper employs directional distance function (DDF) and the global Malmquist–Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China’s 36 industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all industrial sectors, which indicates that the growth of industrial economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor.
Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy
This paper employs directional distance function (DDF) and the global Malmquist–Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China’s 36 industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all industrial sectors, which indicates that the growth of industrial economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor.
Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy
Chaofan Chen (Autor:in) / Qingxin Lan (Autor:in) / Ming Gao (Autor:in) / Yawen Sun (Autor:in)
2018
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
China’s industrial economy , green total factor productivity , determinants , directional distance function , global Malmquist–Luenberger index , dynamic panel data model , Environmental effects of industries and plants , TD194-195 , Renewable energy sources , TJ807-830 , Environmental sciences , GE1-350
Metadata by DOAJ is licensed under CC BY-SA 1.0
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